{"title":"参数不确定条件下具有H∞镇定的炼钢系统轧钢厂节能方案","authors":"V. M. Vaidyan, V. Shijoh, S. Sasikumaran","doi":"10.1109/SPC.2013.6735125","DOIUrl":null,"url":null,"abstract":"In conventional approaches of operation of steel rolling mills, even though Integral Proportional (IP) speed/Neural controllers were used, unfortunately the energy efficiency is not taken into account. This incurs lot of losses in terms of electrical energy and overhead costs. Reduction of energy consumed is critical for reaching a sustainable future. A new approach with maximum efficiency operation is introduced here which ensures energy efficiency and profitable operation of steel rolling mills. Also in industrial applications, armature resistance, armature inductance, moment of inertia, and friction coefficient vary as the operating conditions of the steel rolling mill change. To address parameter uncertainty issues, an H∞ control based approach is used to ensure robustness in multiple parameter uncertainties along with simultaneous energy efficient operation of steel rolling mills. A profitable robust energy efficient approach for steel rolling mills which can be used in real time mills is the result as the proposed robust and efficient operation ensures less overhead and in turn profit in industry. System was modeled from first principles and then was simulated in Matlab environment. The results confirm that the system has better efficiency. And also in validation it confirms system is stable even in multiple parameter uncertainties and load perturbations.","PeriodicalId":198247,"journal":{"name":"2013 IEEE Conference on Systems, Process & Control (ICSPC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy saving scheme for steel rolling mills in steel manufacturing system with H∞ stabilization in parameter uncertainties\",\"authors\":\"V. M. Vaidyan, V. Shijoh, S. Sasikumaran\",\"doi\":\"10.1109/SPC.2013.6735125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In conventional approaches of operation of steel rolling mills, even though Integral Proportional (IP) speed/Neural controllers were used, unfortunately the energy efficiency is not taken into account. This incurs lot of losses in terms of electrical energy and overhead costs. Reduction of energy consumed is critical for reaching a sustainable future. A new approach with maximum efficiency operation is introduced here which ensures energy efficiency and profitable operation of steel rolling mills. Also in industrial applications, armature resistance, armature inductance, moment of inertia, and friction coefficient vary as the operating conditions of the steel rolling mill change. To address parameter uncertainty issues, an H∞ control based approach is used to ensure robustness in multiple parameter uncertainties along with simultaneous energy efficient operation of steel rolling mills. A profitable robust energy efficient approach for steel rolling mills which can be used in real time mills is the result as the proposed robust and efficient operation ensures less overhead and in turn profit in industry. System was modeled from first principles and then was simulated in Matlab environment. The results confirm that the system has better efficiency. And also in validation it confirms system is stable even in multiple parameter uncertainties and load perturbations.\",\"PeriodicalId\":198247,\"journal\":{\"name\":\"2013 IEEE Conference on Systems, Process & Control (ICSPC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Conference on Systems, Process & Control (ICSPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPC.2013.6735125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Conference on Systems, Process & Control (ICSPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPC.2013.6735125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy saving scheme for steel rolling mills in steel manufacturing system with H∞ stabilization in parameter uncertainties
In conventional approaches of operation of steel rolling mills, even though Integral Proportional (IP) speed/Neural controllers were used, unfortunately the energy efficiency is not taken into account. This incurs lot of losses in terms of electrical energy and overhead costs. Reduction of energy consumed is critical for reaching a sustainable future. A new approach with maximum efficiency operation is introduced here which ensures energy efficiency and profitable operation of steel rolling mills. Also in industrial applications, armature resistance, armature inductance, moment of inertia, and friction coefficient vary as the operating conditions of the steel rolling mill change. To address parameter uncertainty issues, an H∞ control based approach is used to ensure robustness in multiple parameter uncertainties along with simultaneous energy efficient operation of steel rolling mills. A profitable robust energy efficient approach for steel rolling mills which can be used in real time mills is the result as the proposed robust and efficient operation ensures less overhead and in turn profit in industry. System was modeled from first principles and then was simulated in Matlab environment. The results confirm that the system has better efficiency. And also in validation it confirms system is stable even in multiple parameter uncertainties and load perturbations.